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"Open Source Models with Hugging Face" course empowers you with the skills to leverage open-source models from the Hugging Face Hub for various tasks in NLP, audio, image, and multimodal domains.
Spam Detector is a Data Science Project built using Pytorch and Hugging Face library. Used BERT model based on Transformer Architecture and got 99.97% accuracy on train set and 98.76% accuracy on test set.
Deployed an interactive web platform for exploring and utilizing language models. Features include real-time text analysis and translation, built with Django for robust performance and scalability
Successfully developed a fine-tuned BERT transformer model which can accurately classify symptoms to their corresponding diseases upto an accuracy of 89%.
Successfully developed a fine-tuned DistilBERT transformer model which can accurately predict the overall sentiment of a piece of financial news up to an accuracy of nearly 81.5%.